Bayesian inference for Cox proportional hazard models with partial likelihoods, nonlinear covariate effects and correlated observations

We propose a flexible and scalable approximate Bayesian inference methodology for the Cox Proportional Hazards model with partial likelihood. The model we consider includes nonlinear covariate effects and correlated survival times. The proposed method is based on nested approximations and adaptive q...

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Detalles Bibliográficos
Autores principales: Zhang, Ziang, Stringer, Alex, Brown, Patrick, Stafford, Jamie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2022
Materias:
Original Research Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9814026/
https://www.ncbi.nlm.nih.gov/pubmed/36317395
http://dx.doi.org/10.1177/09622802221134172

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9814026/
https://www.ncbi.nlm.nih.gov/pubmed/36317395
http://dx.doi.org/10.1177/09622802221134172

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